• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.18-24
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• 2020

When a damage occurs in the nuclear fuel burning in the reactor, fission products that should be in the nuclear fuel rod are released into the reactor coolant. In this case, sipping test, a series of non-destructive inspection methods, are used to find leakage in nuclear fuel assemblies during the power plant overhaul period. In addition, the sipping test is also used to check the integrity of the spent fuel for moving to an intermediate dry storage, which is carried out as the first step of nuclear decommissioning, . In this paper, the principle and characteristics of the sipping test are described. The structure of the sipping inspection equipment is largely divided into a suction device that collects fissile material emitted from a damaged assembly and an analysis device that analyzes their nuclides. In order to make good use of the sipping technology, the radioactive level behavior of the primary system coolant and major damage mechanisms in the event of nuclear fuel damage are also introduced. This will be a reference for selecting an appropriate sipping method when dismantling a nuclear power plant in the future.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.578-595
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• 2020

Submarine pressure hulls must withstand high hydraulic pressure and be free of defects. To improve the precision of defect detection, we herein examined different probes for optimal defect assessment by applying the Phased Array Ultrasonic Testing (PAUT) method. Two sets of probe design parameters were selected by considering pressure hull characteristics and analyzed through modeling. PAUT probes were applied, and defect assessment results were compared based on ultrasonic signals of various simulated defects in specimens designed to be the same as actual pressure hulls. The final selected design parameters for the submarine probe, which were designed to minimize the grating lobe of wave interference effect and improve the ultrasonic resolution of pressure hull welds, were identified through the experiment. The improvement in the probe's ability to detect defects in a pressure hull was verified. Furthermore, the accuracy of defect length measurement was improved, enhancing the applicability of the technique.

• Steel and Composite Structures
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• v.39 no.1
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• pp.81-93
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• 2021

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study offers novel methodologies for the early prediction of this parameter. Artificial neural network (ANN), which is a leading predictive method, is synthesized with two metaheuristic algorithms, namely atom search optimization (ASO) and equilibrium optimizer (EO) to achieve an optimal tuning of the weights and biases. The models are applied to data collected from the published literature. The sensitivity of the ASO and EO to the population size is first investigated, and then, proper configurations of the ASO-NN and EO-NN are compared to the conventional ANN. Evaluating the prediction results revealed the excellent efficiency of EO in optimizing the ANN. Accuracy improvements attained by this algorithm were 13.26 and 11.41% in terms of root mean square error and mean absolute error, respectively. Moreover, it raised the correlation from 0.89958 to 0.92722. This is while the results of the conventional ANN were slightly better than ASO-NN. The EO was also a faster optimizer than ASO. Based on these findings, the combination of the ANN and EO can be an efficient non-destructive tool for predicting the STS.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.186-192
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• 2022

Flow accelerated corrosion (FAC) is a type of pipe corrosion in which the pipe thickness decreases depending on the fluid flow conditions. In nuclear power plants, FAC mainly occurs in the carbon steel pipes of a secondary system. However, because the temperature of a secondary system pipe is over 150 ℃, in situ monitoring using a conventional ultrasonic non-destructive testing method is difficult. In our previous study, we developed a waveguide ultrasonic thickness measurement system. In this study, we applied a waveguide ultrasonic thickness measurement system to monitor the thinning of the pipe according to the change in pH. The Korea Atomic Energy Research Institute installed FAC-proof facilities, enabling the monitoring of internal fluid flow conditions, which were fixed for ~1000 h to analyze the effect of the pH. The measurement system operated without failure for ~3000 h and the pipe thickness was found to be reduced by ~10% at pH 9 compared to that at pH 7. The thickness of the pipe was measured using a microscope after the experiment, and the reliability of the system was confirmed with less than 1% error. This technology is expected to also be applicable to the thickness-reduction monitoring of other high-temperature materials.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.17-21
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• 2022

In this study, we wanted to examine the new vulnerability 'Dirty Pipe' that is founded in Linux kernel. how it's exploited and what is the limitation, where it's existed, and overcome techniques and analysis of the Linux kernel package. The study of the method used the hmark[1] program to check the vulnerabilities. Hmark is a whitebox testing tool that helps to analyze the vulnerability based on static whitebox testing and automated verification. For this purpose of our study, we analyzed Linux kernel code that is downloaded from an open-source website. Then by analyzing the hmark tool results, we identified in which file of the kernel it exists, cvss level, statistically depicted vulnerabilities on graph which is easy to understand. Furthermore, we will talk about some software we can use to analyze a vulnerability and how hmark software works. In the case of the Dirty Pipe vulnerability in Linux allows non-privileged users to execute malicious code capable of a host of destructive actions including installing backdoors into the system, injecting code into scripts, altering binaries used by elevated programs, and creating unauthorized user profiles. This bug is being tracked as CVE-2022-0847 and has been termed "Dirty Pipe"[2] since it bears a close resemblance to Dirty Cow[3], and easily exploitable Linux vulnerability from 2016 which granted a bad actor an identical level of privileges and powers.

• Composites Research
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• v.20 no.3
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• pp.31-36
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• 2007

A quantitative prediction method for initial crack length in a carbon/epoxy (CF/EP) composite beam using active piezoelectric transducers was established in this study. Wavelet Transform (WT)-based signal processing and identification technique in time-frequency domain was developed to facilitate the determination of damage presence and severity. Dynamic response of a CF/EP composites beam containing a continuously expanding crack, coupled with a pair of active piezoelectric disks, was examined under a narrow band excitation, and then applied with the proposed signal processing technique.

• Steel and Composite Structures
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• v.45 no.2
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• pp.281-291
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• 2022

Surmounting complexities in analyzing the mechanical parameters of concrete entails selecting an appropriate methodology. This study integrates a novel metaheuristic technique, namely satin bowerbird optimizer (SBO) with artificial neural network (ANN) for predicting uniaxial compressive strength (UCS) of concrete. For this purpose, the created hybrid is trained and tested using a relatively large dataset collected from the published literature. Three other new algorithms, namely Henry gas solubility optimization (HGSO), sunflower optimization (SFO), and vortex search algorithm (VSA) are also used as benchmarks. After attaining a proper population size for all algorithms, the Utilizing various accuracy indicators, it was shown that the proposed ANN-SBO not only can excellently analyze the UCS behavior, but also outperforms all three benchmark hybrids (i.e., ANN-HGSO, ANN-SFO, and ANN-VSA). In the prediction phase, the correlation indices of 0.87394, 0.87936, 0.95329, and 0.95663, as well as mean absolute percentage errors of 15.9719, 15.3845, 9.4970, and 8.0629%, calculated for the ANN-HGSO, ANN-SFO, ANN-VSA, and ANN-SBO, respectively, manifested the best prediction performance for the proposed model. Also, the ANN-VSA achieved reliable results as well. In short, the ANN-SBO can be used by engineers as an efficient non-destructive method for predicting the UCS of concrete.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.7-13
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• 2023

Nowadays, traffic congestion is emerging as a major problem due to the rapid population growth and the increase in automobiles. The train is a convenient means of transportation that can efficiently solve these problems. Trains have been developed in line with human aspirations for a long time, but research on safety is still insufficient. This study aims to check safety by conducting static tests and fatigue tests on bogie frames, and to help develop bogie frames in the future. For the static test, a strain gauge was attached to the point where the local stress concentration was expected beforehand, and the result value was derived, compared with existing theories, and expressed as a Goodman diagram. In the fatigue test, a total of 10 million loads were applied over three stages, and no cracks appeared in the non-destructive test conducted after each stage. Both tests were conducted according to the strict test method of the bogie frame presented by the UIC Code. It satisfied both fatigue life and strength evaluation criteria and was judged to be a bogie frame usable for safe train production.

• Food Science and Preservation
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• v.30 no.2
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• pp.224-234
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• 2023

We analyzed the major quality characteristics of red pepper powders from various regions and predicted these characteristics nondestructively using shortwave infrared hyperspectral imaging (HSI) technology. We conducted partial least squares regression analysis on 70% (n=71) of the acquired hyperspectral data of the red pepper powders to examine the major quality characteristics. R_c² values of ≥0.8 were obtained for the ASTA color value (0.9263) and capsaicinoid content (0.8310). The developed quality prediction model was validated using the remaining 30% (n=35) of the hyperspectral data; the highest accuracy was achieved for the ASTA color value (R_p²=0.8488), and similar validity levels were achieved for the capsaicinoid and moisture contents. To increase the accuracy of the quality prediction model, we conducted spectrum preprocessing using SNV, MSC, SG-1, and SG-2, and the model's accuracy was verified. The results indicated that the accuracy of the model was most significantly improved by the MSC method, and the prediction accuracy for the ASTA color value was the highest for all the spectrum preprocessing methods. Our findings suggest that the quality characteristics of red pepper powders, even powders that do not conform to specific variables such as particle size and moisture content, can be predicted via HSI.

• Land and Housing Review
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• v.15 no.3
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• pp.153-164
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• 2024

Structural health monitoring involves performance evaluation based on measurements for maintenance purposes. By back-calculating measured Frequency Response Function (FRF) data, the concept of effective mass was introduced and applied to the performance evaluation of structural members. An identification method was proposed that uses participation factors to estimate the dynamic parameters and the strength of concrete of structural members. The appropriateness of these methods for identifying dynamic parameters and concrete strength of structural members was validated through experimental results, proving their utility in non-destructive testing for concrete strength.